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Knowledge library

Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.

Quant Q&A
20,364 documents
SuperMind
12,226 documents
OKX Learn
8,431 documents
Strategy library
7,910 documents
MQL5 code base
7,090 documents
BigQuant
3,481 documents
Bitget Academy
3,298 documents
MQL5 articles
3,012 documents
TradingView scripts
1,976 documents
ProRealCode
1,507 documents
Deribit Insights
1,232 documents
Machine Learning for Trading
1,124 documents
arXiv papers
1,033 documents
Amberdata research
766 documents
FMZ forum
682 documents
FMZ digest
662 documents
vn.py community
560 documents
QuantInsti blog
511 documents
Galaxy Research
340 documents
QuantStart
246 documents
Stratmill research code
219 documents
Robot Wealth
195 documents
NautilusTrader
191 documents
Hummingbot docs
181 documents
Paradigm research
175 documents
Lumibot
164 documents
Kraken Learn
163 documents
Quant course library
157 documents
OctoBot
152 documents
Cryptohopper blog
144 documents
Systematic trading blog (Rob Carver)
132 documents
Qlib
116 documents
TqSdk
86 documents
Quantpedia
86 documents
Hyperliquid docs
79 documents
Freqtrade
68 documents
Hudson & Thames
62 documents
Awesome Systematic Trading
61 documents
backtrader
54 documents
vn.py
50 documents
Binance API docs
45 documents
Quantopian lectures
45 documents
FMZ guides
38 documents
pysystemtrade
34 documents
Freqtrade docs
32 documents
quant-trading
31 documents
FinRL
28 documents
Zipline
22 documents
FMZ live strategies
21 documents
Jesse
17 documents
pyfolio
16 documents
Alphalens
14 documents
WonderTrader
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

3,481 documents

BigQuant

This short forum exchange addresses an error in a regression-evaluation workflow that reports a missing label. The response says the problem cannot be diagnosed precisely without details about the task, then recommends first defining what quantity the model…

Machine learningStatisticsBacktesting
BigQuant

The document records a user’s question about a trading platform’s order function: sell instructions appear to execute at the following day’s close rather than the day they are issued. The issue affects holding-period exits and closing-price take-profit or…

ExecutionBacktestingRisk management
BigQuant

This report reviews quality-focused Smart Beta investing in overseas and Chinese markets. It describes the approach as an index strategy built from company financial data to capture underlying business quality, then compares product development and index…

Factor investingEquitiesStatisticsBacktesting
BigQuant

This report examines fund advisory services in China, including how third-party fund platforms work with licensed asset managers and how advisory services may evolve. It describes the platforms mainly as places where advisory strategies are presented, with…

China marketsPortfolio constructionEquitiesFixed income
BigQuant

The article examines whether dividend announcements convey information about future company earnings. It argues that prior studies may have missed this link by grouping earnings by fiscal year, which can treat post-announcement earnings as already known.…

EquitiesEvent-drivenStatisticsUS markets
BigQuant

This document describes a chart indicator that draws support, resistance, and trend lines over a configurable number of bars. It was initially used within a short-term scalping approach on five- and fifteen-minute charts, and later as a standalone indicator…

Technical indicatorsBreakout
BigQuant

This article explains random forests through CART decision trees, Gini impurity, bootstrap sampling, and aggregation. Trees are trained on resampled data, while their predictions are combined by voting for classification or averaging for regression. It also…

EquitiesMachine learningFactor investingBacktesting
BigQuant

This report compares ways to measure similarity among funds, including cosine similarity, Euclidean distance, and return correlations. It argues that the choice of measure should follow the intended meaning of “similar”: resemblance in holdings structure,…

Multi-assetPortfolio constructionStatisticsBacktesting
BigQuant

This short discussion explains how to compute a running total of traded amount separately for each stock in a multi-instrument dataset. A single cumulative sum across the full table combines all instruments, so the suggested approach groups rows by…

EquitiesStatistics
BigQuant

The document introduces factor research as a way to study characteristics that may help explain the returns and risks of financial assets. It names market capitalization, quality, momentum, low volatility, and yield as examples of factors that researchers…

Factor investingStatisticsPortfolio constructionRisk management
BigQuant

This example implements a Dual Thrust breakout strategy on a futures contract using daily bars. It calculates a range from the prior five completed sessions: the larger of the highest high minus the lowest close, or the highest close minus the lowest low.…

FuturesBreakoutTrend followingExecution
BigQuant

This research note outlines an extension to traditional risk parity. Standard risk parity assigns equal contributions to portfolio volatility, but this approach accounts for only variance and can leave exposure to skewness and kurtosis uneven. Those higher…

Multi-assetPortfolio constructionRisk managementStatistics
BigQuant

The document summarizes research on whether investors react differently to corporate announcements made before major holidays. The study examines US stock repurchases, equity issuance, mergers, and quarterly earnings announcements from 1984 to 2012,…

EquitiesEvent-drivenSentimentStatistics
BigQuant

The document catalogs the 158 Alpha158 features used in quantitative equity research. It groups formulas into candlestick shape and normalized price features; trend measures such as returns, moving averages, regression slopes, fit, and residuals; and…

EquitiesFactor investingTechnical indicatorsStatistics
BigQuant

This report describes a multi-factor event rotation approach for finding stock-related events that may be attracting market attention. It considers events involving shareholder behavior, dividend policies, earnings forecasts and growth reports, and private…

EquitiesEvent-drivenFactor investingStatistics
BigQuant

This essay argues that traders should pass on marginal setups and act only when a trade strongly meets their criteria. It frames selectivity as a way to reduce unnecessary decisions and make accepting losses more manageable. It also emphasizes studying wins…

Risk managementStatistics
BigQuant

This research summary describes a method for forecasting year-over-year inventory growth across six products in China’s ferrous commodity chain. It treats inventory as an indicator of relative supply and demand, while noting that true inventory is difficult…

CommoditiesChina marketsMachine learningStatistics
BigQuant

This brief troubleshooting note explains one cause of an empty-data error in a futures backtest. It says that the exchange’s contract symbol convention matters: for Dalian Commodity Exchange contracts, the letter portion should be lowercase, and using…

FuturesBacktesting
BigQuant

This report proposes classifying equity sectors by how their excess returns relate to economic conditions. It questions existing Chinese cyclical and noncyclical sector indexes, then measures lead-lag correlations between China Securities Index industry…

EquitiesChina marketsFactor investingBacktesting
BigQuant

The document describes a liquidity premium factor built from buy-side limit order book data. For a chosen trade amount, the method simulates execution against displayed orders, adding interpolated virtual orders as needed, and compares the resulting market…

EquitiesFactor investingMarket microstructureStatistics
BigQuant

This article proposes interpreting a sharp drop after a news-driven, limit-up move as a possible shakeout before another advance. Its suggested filters are a month or more of relatively quiet consolidation with range contained within 20%, a stock near the…

EquitiesChina marketsBreakoutMomentum
BigQuant

The document introduces Bayes’ theorem as a way to update the probability of an event after receiving new evidence. It defines the prior probability, likelihood, marginal probability, and posterior probability, and gives the formula relating them. It also…

StatisticsMachine learningEquitiesRisk management
BigQuant

This Chinese equities study proposes quantifying unusual intraday stock behavior by measuring how often a stock moves against a market index. It uses correlation as a screening tool to identify these divergence events, then treats them as event-driven…

China marketsEquitiesEvent-drivenStatistics
BigQuant

This Chinese-language monthly and weekly product review reports results for several China equity strategies in May 2018. It covers multi-factor index enhancement portfolios linked to the CSI 300 and CSI 500, a short-horizon price-volume model, AI stock…

China marketsEquitiesFactor investingMomentum